Loading Data with SQL

This topic describes several ways to load data to OmniSci using SQL commands.

• If there is a potential for duplicate entries, and you want to avoid loading duplicate rows, see How can I avoid creating duplicate rows? on the Troubleshooting page.

• If a source file uses a reserved word, OmniSci automatically adds an underscore at the end of the reserved word. For example, year is converted to year_.

COPY FROM

CSV/TSV Import

Use the following syntax for CSV and TSV files:

COPY <table> FROM '<file pattern>' [WITH (<property> = value, ...)];

<file pattern> must be local on the server. The file pattern can contain wildcards if you want to load multiple files. In addition to CSV, TSV, and TXT files, you can import compressed files in TAR, ZIP, 7-ZIP, RAR, GZIP, BZIP2, or TGZ format.

COPY FROM appends data from the source into the target table. It does not truncate the table or overwrite existing data.

You can import client-side files (\copy command in omnisql) but it is significantly slower. For large files, OmniSci recommends that you first scp the file to the server, and then issue the COPY command.

OmniSci supports Latin-1 ASCII format and UTF-8. If you want to load data with another encoding (for example, UTF-16), convert the data to UTF-8 before loading it to OmniSci.

Available properties in the optional WITH clause are described in the following table.

Parameter	Description	Default Value
array_delimiter	A single-character string for the delimiter between input values contained within an array.	, (comma)
array_marker	A two-character string consisting of the start and end characters surrounding an array.	{ }(curly brackets). For example, data to be inserted into a table with a string array in the second column (for example, BOOLEAN, STRING[], INTEGER) can be written as true,{value1,value2,value3},3
buffer_size	Size of the input file buffer, in bytes.	8388608
delimiter	A single-character string for the delimiter between input fields; most commonly: , for CSV files \t for tab-delimited files Other delimiters include | ,~, ^, and;. Note: OmniSci does not use file extensions to determine the delimiter.	',' (CSV file)
escape	A single-character string for escaping quotes.	'"' (double quote)
header	Either 'true' or 'false', indicating whether the input file has a header line in Line 1 that should be skipped.	'true'
line_delimiter	A single-character string for terminating each line.	'\n'
lonlat	In OmniSci, POINT fields require longitude before latitude. Use this parameter based on the order of longitude and latitude in your source data.	'true'
max_reject	Number of records that the COPY statement allows to be rejected before terminating the COPY command. Records can be rejected for a number of reasons, including invalid content in a field, or an incorrect number of columns. The details of the rejected records are reported in the ERROR log. COPY returns a message identifying how many records are rejected. The records that are not rejected are inserted into the table, even if the COPY stops because the max_reject count is reached. Note: If you run the COPY command from OmniSci Immerse, the COPY command does not return messages to Immerse once the SQL is verified. Immerse does not show messages about data loading, or about data-quality issues that result in max_reject triggers.	100,000
nulls	A string pattern indicating that a field is NULL.	An empty string, 'NA', or \N
parquet	Import data in Parquet format. Parquet files can be compressed using Snappy. Other archives such as .gz or .zip must be unarchived before you import the data.	'false'
plain_text	Indicates that the input file is plain text so that it bypasses the libarchive decompression utility.	CSV, TSV, and TXT are handled as plain text.
quote	A single-character string for quoting a field.	" (double quote). All characters inside quotes are imported “as is,” except for line delimiters.
quoted	Either 'true' or 'false', indicating whether the input file contains quoted fields.	'true'
threads	Number of threads for performing the data import.	Number of CPU cores on the system

By default, the CSV parser assumes one row per line. To import a file with multiple lines in a single field, specify threads = 1 in the WITH clause.

Examples

COPY tweets FROM '/tmp/tweets.csv' WITH (nulls = 'NA'); 
COPY tweets FROM '/tmp/tweets.tsv' WITH (delimiter = '\t', quoted = 'false'); 
COPY tweets FROM '/tmp/*' WITH (header='false'); 
COPY trips FROM '/mnt/trip/trip.parquet/part-00000-0284f745-1595-4743-b5c4-3aa0262e4de3-c000.snappy.parquet' with (parquet='true');

Geo Import

You can use COPY FROM to import geo files. You can create the table based on the source file and then load the data:

COPY tableName FROM 'source' WITH (geo='true', ...);

You can also append data to an existing, predefined table:

COPY FROM 'source' WITH (geo='true', ...);

Use the following syntax, depending on the file source.

Source	Syntax
Local server	COPY [tableName] FROM '/filepath' WITH (geo='true', ...);
Web site	COPY [tableName] FROM '[http `	_https_]://_website/filepath_' WITH (geo='true', ...);`
Amazon S3	COPY [tableName] FROM 's3://bucket/filepath' WITH (geo='true', s3_region='region', s3_access_key='accesskey', s3_secret_key='secretkey', ... );

• If you are using COPY FROM to load to an existing table, the field type must match the metadata of the source file. If it does not, COPY FROM throws an error and does not load the data.

• COPY FROM appends data from the source into the target table. It does not truncate the table or overwrite existing data.

• Supported DATE formats when using COPY FROM include mm/dd/yyyy, dd-mmm-yy, yyyy-mm-dd, and dd/mmm/yyyy.

• COPY FROM fails for records with latitude or longitude values that have more than 4 decimal places.

The following WITH options are available for geo file imports from all sources.

Parameter	Description	Default Value
geo_assign_render_groups	Enable or disable automatic render group assignment for polygon imports; can be true or false. If polygons are not needed for rendering, set this to false to speed up import.	true
geo_coords_type	Coordinate type used; must be geography.	N/A
geo_coords_encoding	Coordinates encoding; can be geoint(32) or none.	geoint(32)
geo_coords_srid	Coordinates spatial reference; must be 4326 (WGS84 longitude/latitude).	N/A
geo_explode_collections	Explodes MULTIPOLYGON, MULTILINESTRING, or MULTIPOINT geo data into multiple rows in a POLYGON, LINESTRING, or POINT column, with all other columns duplicated. When importing from a WKT CSV with a MULTIPOLYGON column, the table must have been manually created with a POLYGON column. Similarly, a MULTILINESTRING column must be created with LINESTRING, and a MULTIPOINT column must be created with POINT. Storing MULTILINESTRING or MULTIPOINT directly is not supported, but can be exploded into a LINESTRING or POINT column. When importing from a geo file, the table is automatically created with the correct type of column. When the input column contains a mixture of MULTI and single geo, the MULTI geo are exploded, but the singles are imported normally. For example, a column containing five two-polygon MULTIPOLYGON rows and five POLYGON rows imports as a POLYGON column of fifteen rows.	false

Currently, a manually created geo table can have only one geo column. If it has more than one, import is not performed.

The following file types are supported:

• ESRI Shapefile (.shp)

• ESRI file geodatabase (.gdb)

• GeoJSON (.geojson, .json, .geojson.gz, .json.gz)

• KML (.kml, kmz)

• File bundles:

  • .zip

  • .tar

  • .tar.gz

  • .tgz

An ESRI file geodatabase can have multiple layers, and importing it results in the creation of one table for each layer in the file. This behavior differs from that of importing shapefiles, GeoJSON, or KML files, which results in a single table. For more information, see Importing an ESRI File Geodatabase.

The first compatible file (.shp, .gdb, .geojson, .kml) in the bundle is loaded; subfolders are traversed until a compatible file is found. The rest of the contents in the bundle are ignored. If the bundle contains multiple filesets, unpack the file manually and specify it for import.

For more information about importing specific geo file formats, see Importing Geospatial Files.

CSV files containing WKT strings are not considered geo files and should not be parsed with the geo='true' option. When importing WKT strings from CSV files, you must create the table first. The geo column type and encoding are specified as part of the DDL. For example, for a polygon with no encoding, try the following:

ggpoly GEOMETRY(POLYGON, 4326) ENCODING COMPRESSED(32)

SQLImporter

SQLImporter is a Java utility run at the command line. It runs a SELECT statement on another database through JDBC and loads the result set into OmniSciDB.

Usage

java -cp [OmniSci utility jar file]:[3rd party JDBC driver]
SQLImporter
-u <userid>; -p <password>; [(--binary|--http|--https [--insecure])]
-s <omnisci server host> -db <omnsci db> --port <omnisci server port>
[-d <other database JDBC drive class>] -c <other database JDBC connection string>
-su <other database user> -sp <other database user password> -su <other database sql statement>
-t <OmniSci target table> -b <transfer buffer size> -f <table fragment size>
[-tr] -i <init commands file>

Flags

-r                             Row load limit 
-h,--help                      Help message
-r <arg>;                      Row load limit 
-h,--help                      Help message 
-u,--user <arg>;               OmniSci user 
-p,--passwd <arg>;             OmniSci password 
--binary                       Use binary transport to connect to OmniSci 
--http                         Use http transport to connect to OmniSci 
--https                        Use https transport to connect to OmniSci 
-s,--server <arg>;             OmniSci Server 
-db,--database <arg>;          OmniSci Database 
--port <arg>;                  OmniSci Port 
--ca-trust-store <arg>;        CA certificate trust store 
--ca-trust-store-passwd <arg>; CA certificate trust store password 
--insecure <arg>;              Inseure TLS - Do not validate server OmniSci server credentials 
-d,--driver <arg>;             JDBC driver class 
-c,--jdbcConnect <arg>;        JDBC connection string 
-su,--sourceUser <arg>;        Source user 
-sp,--sourcePasswd <arg>;      Source password 
-ss,--sqlStmt <arg>;           SQL Select statement 
-t,--targetTable <arg>;        OmniSci Target Table 
-b,--bufferSize <arg>;         Transfer buffer size 
-f,--fragmentSize <arg>;       Table fragment size 
-tr,--truncate                 Truncate table if it exists 
-i,--initializeFile <arg>;     File containing init command for DB

OmniSci recommends that you use a service account with read-only permissions when accessing data from a remote database.

In release 4.6 and higher, the user ID (-u) and password (-p) flags are required. If your password includes a special character, you must escape the character using a backslash (\).

If the table does not exist in OmniSciDB, SQLImporter creates it. If the target table in OmniSciDB does not match the SELECT statement metadata, SQLImporter fails.

If the truncate flag is used, SQLImporter truncates the table in OmniSciDB before transferring the data. If the truncate flag is not used, SQLImporter appends the results of the SQL statement to the target table in OmniSciDB.

The -i argument provides a path to an initialization file. Each line of the file is sent as a SQL statement to the remote database. You can use -i to set additional custom parameters before the data is loaded.

The SQLImporter string is case-sensitive. Incorrect case returns the following:

Error: Could not find or load main class com.mapd.utility.SQLimporter

PostgreSQL/PostGIS Support

You can migrate geo data types from a PostgreSQL database. The following table shows the correlation between PostgreSQL/PostGIS geo types and OmniSci geo types.

PostgreSQL/PostGIS Type	OmniSci Type
point	point
lseg	linestring
linestring	linestring
polygon	polygon
multipolygon	multipolygon

Other PostgreSQL types, including circle, box, and path, are not supported.

OmniSciDB Example

java -cp /opt/omnisci/bin/mapd-1.0-SNAPSHOT-jar-with-dependencies.jar 
com.mapd.utility.SQLImporter -u admin -p HyperInteractive -db omnisci --port 6274 
-t mytable -su admin -sp HyperInteractive -c "jdbc:omnisci:myhost:6274:omnisci" 
-ss "select * from mytable limit 1000000000"

By default, 100,000 records are selected from OmniSciDB. To select a larger number of records, use the LIMIT statement.

Hive Example

java -cp /opt/omnisci/bin/mapd-1.0-SNAPSHOT-jar-with-dependencies.jar:/hive-jdbc-1.2.1000.2.6.1.0-129-standalone.jar
com.mapd.utility.SQLImporter
-u user -p password
-db OmniSci_database_name --port 6274 -t OmniSci_table_name
-su source_user -sp source_password
-c "jdbc:hive2://server_address:port_number/database_name"
-ss "select * from source_table_name"

Google Big Query Example

java -cp /opt/omnisci/bin/omnisci-1.0-SNAPSHOT-jar-with-dependencies-BQ.jar:./GoogleBigQueryJDBC42.jar:
./google-oauth-client-1.22.0.jar:./google-http-client-jackson2-1.22.0.jar:./google-http-client-1.22.0.jar:./google-api-client-1.22.0.jar:
./google-api-services-bigquery-v2-rev355-1.22.0.jar 
com.mapd.utility.SQLImporter
-d com.simba.googlebigquery.jdbc42.Driver 
-u user -p password
-db OmniSci_database_name --port 6274 -t OmniSci_table_name
-su source_user -sp source_password 
-c "jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;ProjectId=project-id;OAuthType=0;
OAuthServiceAcctEmail==[e-mail];OAuthPvtKeyPath=/home/simba/myproject.json;"
-ss "select * from schema.source_table_name"

PostgreSQL Example

java -cp /opt/omnisci/bin/mapd-1.0-SNAPSHOT-jar-with-dependencies.jar:/tmp/postgresql-42.2.5.jar 
com.mapd.utility.SQLImporter 
-u user -p password
-db OmniSci_database_name --port 6274 -t OmniSci_table_name
-su source_user -sp source_password 
-c "jdbc:postgresql://127.0.0.1/postgres"
-ss "select * from schema_name.source_table_name"

SQLServer Example

java -cp /opt/omnisci/bin/mapd-1.0-SNAPSHOT-jar-with-dependencies.jar:/path/sqljdbc4.jar
com.mapd.utility.SQLImporter
-d com.microsoft.sqlserver.jdbc.SQLServerDriver 
-u user -p password
-db OmniSci_database_name --port 6274 -t OmniSci_table_name
-su source_user -sp source_password 
-c "jdbc:sqlserver://server:port;DatabaseName=database_name"
-ss "select top 10 * from dbo.source_table_name"

MySQL Example

java -cp /opt/omnisci/bin/mapd-1.0-SNAPSHOT-jar-with-dependencies.jar:mysql/mysql-connector-java-5.1.38-bin.jar
com.mapd.utility.SQLImporter 
-u user -p password
-db OmniSci_database_name --port 6274 -t OmniSci_table_name
-su source_user -sp source_password 
-c "jdbc:mysql://server:port/DatabaseName=database_name"
-ss "select * from schema_name.source_table_name"

StreamInsert

Stream data into OmniSciDB by attaching the StreamInsert program to the end of a data stream. The data stream can be another program printing to standard out, a Kafka endpoint, or any other real-time stream output. You can specify the appropriate batch size, according to the expected stream rates and your insert frequency. The target table must exist before you attempt to stream data into the table.

<data stream> | StreamInsert <table name> <database name> \
{-u|--user} <user> {-p|--passwd} <password> [{--host} <hostname>] \
[--port <port number>][--delim <delimiter>][--null <null string>] \
[--line <line delimiter>][--batch <batch size>][{-t|--transform} \
transformation ...][--retry_count <num_of_retries>] \
[--retry_wait <wait in secs>][--print_error][--print_transform]

Setting	Default	Description
<table_name>	n/a	Name of the target table in OmniSci
<database_name>	n/a	Name of the target database in OmniSci
-u	n/a	User name
-p	n/a	User password
--host	n/a	Name of OmniSci host
--delim	comma (,)	Field delimiter, in single quotes
--line	newline (\n)	Line delimiter, in single quotes
--batch	10000	Number of records in a batch
--retry_count	10	Number of attempts before job fails
--retry_wait	5	Wait time in seconds after server connection failure
--null	n/a	String that represents null values
--port	6274	Port number for OmniSciDB on localhost
`-t	--transform`	n/a	Regex transformation
--print_error	False	Print error messages
--print_transform	False	Print description of transform.
--help	n/a	List options

For more information on creating regex transformation statements, see RegEx Replace.

Example

cat file.tsv | /path/to/omnisci/SampleCode/StreamInsert stream_example \
omnisci --host localhost --port 6274 -u imauser -p imapassword \
--delim '\t' --batch 1000

Importing AWS S3 Files

You can use the SQL COPY FROM statement to import files stored on Amazon Web Services Simple Storage Service (AWS S3) into a OmniSci table, in much the same way you would with local files. In the WITH clause, specify the S3 credentials and region information of the bucket accessed.

COPY <table> FROM '<S3_file_URL>' WITH (s3_access_key = '<key_name>',s3_secret_key = '<key_secret>',s3_region = '<region>');

Access key, secret key, and region are required. For information about AWS S3 credentials, see https://docs.aws.amazon.com/general/latest/gr/aws-sec-cred-types.html#access-keys-and-secret-access-keys.

OmniSci does not support the use of asterisks (*) in URL strings to import items. To import multiple files, pass in an S3 path instead of a file name, and COPY FROM imports all items in that path and any subpath.

Custom S3 Endpoints

OmniSci supports custom S3 endpoints, which allows you to import data from S3-compatible services, such as Google Cloud Storage.

To use custom S3 endpoints, add s3_endpoint to the WITH clause of a COPY FROM statement; for example:

COPY trips FROM 's3://omnisci-importtest-data/trip-data/trip_data_9.gz' WITH (header='true', s3_endpoint='storage.googleapis.com');

For information about interoperability and setup for Google Cloud Services, see Cloud Storage Interoperability.

You can also configure custom S3 enpoints by passing the s3_endpoint field to Thrift import_table.

Examples

The following examples show failed and successful attempts to copy the table trips from AWS S3.

omnisql> COPY trips FROM 's3://omnisci-s3-no-access/trip_data_9.gz';
Exception: failed to list objects of s3 url 's3://omnisci-s3-no-access/trip_data_9.gz': AccessDenied: Access Denied

omnisql> COPY trips FROM 's3://omnisci-s3-no-access/trip_data_9.gz' with (s3_access_key='xxxxxxxxxx',s3_secret_key='yyyyyyyyy');
Exception: failed to list objects of s3 url 's3://omnisci-s3-no-access/trip_data_9.gz': AuthorizationHeaderMalformed: Unable to parse ExceptionName: AuthorizationHeaderMalformed Message: The authorization header is malformed; the region 'us-east-1' is wrong; expecting 'us-west-1'

omnisql> COPY trips FROM 's3://omnisci-testdata/trip.compressed/trip_data_9.csv' with (s3_access_key='xxxxxxxx',s3_secret_key='yyyyyyyy',s3_region='us-west-1');
Result
Loaded: 100 recs, Rejected: 0 recs in 0.361000 secs

The following example imports all the files in the trip.compressed directory.

omnisql> copy trips from 's3://omnisci-testdata/trip.compressed/' with (s3_access_key='xxxxxxxx',s3_secret_key='yyyyyyyy',s3_region='us-west-1');
Result
Loaded: 105200 recs, Rejected: 0 recs in 1.890000 secs

trips Table

The table trips is created with the following statement:

omnisql> \d trips
        CREATE TABLE trips (
        medallion TEXT ENCODING DICT(32),
        hack_license TEXT ENCODING DICT(32),
        vendor_id TEXT ENCODING DICT(32),
        rate_code_id SMALLINT,
        store_and_fwd_flag TEXT ENCODING DICT(32),
        pickup_datetime TIMESTAMP,
        dropoff_datetime TIMESTAMP,
        passenger_count SMALLINT,
        trip_time_in_secs INTEGER,
        trip_distance DECIMAL(14,2),
        pickup_longitude DECIMAL(14,2),
        pickup_latitude DECIMAL(14,2),
        dropoff_longitude DECIMAL(14,2),
        dropoff_latitude DECIMAL(14,2))
WITH (FRAGMENT_SIZE = 75000000);

KafkaImporter

You can ingest data from an existing Kafka producer to an existing table in OmniSci using KafkaImporter on the command line:

KafkaImporter <table_name> <database_name> {-u|--user <user_name> \
{-p|--passwd <user_password>} [{--host} <hostname>] \
[--port <OmniSciDB_port>] [--http] [--https] [--skip-verify] \
[--ca-cert <path>] [--delim <delimiter>] [--batch <batch_size>] \
[{-t|--transform} transformation ...] [retry_count <retry_number>] \
[--retry_wait <delay_in_seconds>] --null <null_value_string> [--quoted true|false] \
[--line <line_delimiter>] --brokers=<broker_name:broker_port> \ 
--group-id=<kafka_group_id> --topic=<topic_type> [--print_error] [--print_transform]

KafkaImporter requires a functioning Kafka cluster. See the Kafka website and the Confluent schema registry documentation.

KafkaImporter Options

Setting	Default	Description
<table_name>	n/a	Name of the target table in OmniSci
<database_name>	n/a	Name of the target database in OmniSci
-u <username>	n/a	User name
-p <password>	n/a	User password
--host <hostname>	localhost	Name of OmniSci host
--port <port_number>	6274	Port number for OmniSciDB on localhost
--http	n/a	Use HTTP transport
--https	n/a	Use HTTPS transport
--skip-verify	n/a	Do not verify validity of SSL certificate
--ca-cert <path>	n/a	Path to the trusted server certificate; initiates an encrypted connection
--delim <delimiter>	comma (,)	Field delimiter, in single quotes
--line <delimiter>	newline (\n)	Line delimiter, in single quotes
--batch <batch_size>	10000	Number of records in a batch
--retry_count <retry_number>	10	Number of attempts before job fails
--retry_wait <seconds>	5	Wait time in seconds after server connection failure
--null <string>	n/a	String that represents null values
--quoted <boolean>	false	Whether the source contains quoted fields
`-t	--transform`	n/a	Regex transformation
--print_error	false	Print error messages
--print_transform	false	Print description of transform
--help	n/a	List options
--group-id <id>	n/a	Kafka group ID
--topic <topic>	n/a	The Kafka topic to be ingested
--brokers <broker_name:broker_port>	localhost:6273	One or more brokers

KafkaImporter Logging Options

KafkaImporter Logging Options
Setting	Default	Description
--log-directory <directory>	mapd_log	Logging directory; can be relative to data directory or absolute
--log-file-name <filename>	n/a	Log filename relative to logging directory; has format KafkaImporter.{SEVERITY}.%Y%m%d-%H%M%S.log
--log-symlink <symlink>	n/a	Symlink to active log; has format KafkaImporter.{SEVERITY}
--log-severity <level>	INFO	Log-to-file severity level: INFO, WARNING, ERROR, or FATAL
--log-severity-clog <level>	ERROR	Log-to-console severity level: INFO, WARNING, ERROR, or FATAL
--log-channels	n/a	Log channel debug info
--log-auto-flush	n/a	Flush logging buffer to file after each message
--log-max-files <files_number>	100	Maximum number of log files to keep
--log-min-free-space <bytes>	20,971,520	Minimum number of bytes available on the device before oldest log files are deleted
--log-rotate-daily	1	Start new log files at midnight
--log-rotation-size <bytes>	10485760	Maximum file size, in bytes, before new log files are created

Configure KafkaImporter to use your target table. KafkaImporter listens to a pre-defined Kafka topic associated with your table. You must create the table before using the KafkaImporter utility. For example, you might have a table named customer_site_visit_events that listens to a topic named customer_site_visit_events_topic.

The data format must be a record-level format supported by OmniSci.

KafkaImporter listens to the topic, validates records against the target schema, and ingests topic batches of your designated size to the target table. Rejected records use the existing reject reporting mechanism. You can start, shut down, and configure KafkaImporter independent of the OmniSciDB engine. If KafkaImporter is running and the database shuts down, KafkaImporter shuts down as well. Reads from the topic are nondestructive.

KafkaImporter is not responsible for event ordering; a streaming platform outside OmniSci (for example, Spark streaming, flink) should handle the stream processing. OmniSci ingests the end-state stream of post-processed events.

KafkaImporter does not handle dynamic schema creation on first ingest, but must be configured with a specific target table (and its schema) as the basis. There is a 1:1 correspondence between target table and topic.

cat tweets.tsv | ./KafkaImporter tweets_small omnisci
-u imauser
-p imapassword
--delim '\t'
--batch 100000
--retry_count 360
--retry_wait 10
--null null
--port 9999
--brokers=localhost:6273
--group-id=testImport1
--topic=tweet

StreamImporter

StreamImporter is an updated version of the StreamInsert utility used for streaming reads from delimited files into OmniSciDB. StreamImporter uses a binary columnar load path, providing improved performance compared to StreamInsert.

You can ingest data from a data stream to an existing table in OmniSci using StreamImporter on the command line.

StreamImporter <table_name> <database_name> {-u|--user <user_name> \
{-p|--passwd <user_password>} [{--host} <hostname>] [--port <OmniSciDB_port>] \
[--http] [--https] [--skipverify] [--ca-cert <path>] [--delim <delimiter>] \
[--null <null string>] [--line <line delimiter>]  [--quoted <boolean>] \
 [--batch <batch_size>] [{-t|--transform} transformation ...] \
[retry_count <number_of_retries>] [--retry_wait <delay_in_seconds>]  \
[--print_error] [--print_transform]

StreamImporter Options

Setting	Default	Description
<table_name>	n/a	Name of the target table in OmniSci
<database_name>	n/a	Name of the target database in OmniSci
-u <username>	n/a	User name
-p <password>	n/a	User password
--host <hostname>	n/a	Name of OmniSci host
--port <port>	6274	Port number for OmniSciDB on localhost
--http	n/a	Use HTTP transport
--https	n/a	Use HTTPS transport
--skip-verify	n/a	Do not verify validity of SSL certificate
--ca-cert <path>	n/a	Path to the trusted server certificate; initiates an encrypted connection
--delim <delimiter>	comma (,)	Field delimiter, in single quotes
--null <string>	n/a	String that represents null values
--line <delimiter>	newline (\n)	Line delimiter, in single quotes
--quoted <boolean>	true	Either true or false, indicating whether the input file contains quoted fields.
--batch <number>	10000	Number of records in a batch
--retry_count <retry_number>	10	Number of attempts before job fails
--retry_wait <seconds>	5	Wait time in seconds after server connection failure
`-t	--transform`	n/a	Regex transformation
--print_error	false	Print error messages
--print_transform	false	Print description of transform
--help	n/a	List options

StreamImporter Logging Options

Setting	Default	Description
--log-directory <directory>	mapd_log	Logging directory; can be relative to data directory or absolute
--log-file-name <filename>	n/a	Log filename relative to logging directory; has format StreamImporter.{SEVERITY}.%Y%m%d-%H%M%S.log
--log-symlink <symlink>	n/a	Symlink to active log; has format StreamImporter.{SEVERITY}
--log-severity <level>	INFO	Log-to-file severity level: INFO, WARNING, ERROR, or FATAL
--log-severity-clog <level>	ERROR	Log-to-console severity level: INFO, WARNING, ERROR, or FATAL
--log-channels	n/a	Log channel debug info
--log-auto-flush	n/a	Flush logging buffer to file after each message
--log-max-files <files_number>	100	Maximum number of log files to keep
--log-min-free-space <bytes>	20,971,520	Minimum number of bytes available on the device before oldest log files are deleted
--log-rotate-daily	1	Start new log files at midnight
--log-rotation-size <bytes>	10485760	Maximum file size, in bytes, before new log files are created

Configure StreamImporter to use your target table. StreamImporter listens to a pre-defined data stream associated with your table. You must create the table before using the StreamImporter utility.

The data format must be a record-level format supported by OmniSci.

StreamImporter listens to the stream, validates records against the target schema, and ingests batches of your designated size to the target table. Rejected records use the existing reject reporting mechanism. You can start, shut down, and configure StreamImporter independent of the OmniSciDB engine. If StreamImporter is running but the database shuts down, StreamImporter shuts down as well. Reads from the stream are non-destructive.

StreamImporter is not responsible for event ordering - a first class streaming platform outside OmniSci (for example, Spark streaming, flink) should handle the stream processing. OmniSci ingests the end-state stream of post-processed events.

StreamImporter does not handle dynamic schema creation on first ingest, but must be configured with a specific target table (and its schema) as the basis.

There is a 1:1 correspondence between target table and a stream record.

cat tweets.tsv | ./StreamImporter tweets_small omnisci
-u imauser
-p imapassword
--delim '\t'
--batch 100000
--retry_count 360
--retry_wait 10
--null null
--port 9999

Importing Data from HDFS with Sqoop

You can consume a CSV or Parquet file residing in HDFS (Hadoop Distributed File System) into OmniSciDB.

Copy the OmniSci JDBC driver into the Apache Sqoop library, normally found at /usr/lib/sqoop/lib/.

Example

The following is a straightforward import command. For more information on options and parameters for using Apache Sqoop, see the user guide at sqoop.apache.org.

sqoop-export --table iAmATable \
--export-dir /user/cloudera/ \
--connect "jdbc:omnisci:000.000.000.0:6274:omnisci" \
--driver com.omnisci.jdbc.OmniSciDriver \
--username imauser \
--password imapassword \
--direct \
--batch

The --connect parameter is the address of a valid JDBC port on your OmniSci instance.

Troubleshooting: Avoiding Duplicate Rows

To detect duplication prior to loading data into OmniSciDB, you can perform the following steps. For this example, the files are labeled A,B,C...Z.

1. Load file A into table MYTABLE.

2. Run the following query.

   select count(t1.uniqueCol) as dups from MYTABLE t1 join MYTABLE t2 on t1.uCol = t2.uCol;

   There should be no rows returned; if rows are returned, your first A file is not unique.

3. Load file B into table TEMPTABLE.

4. Run the following query.

   select count(t1.uniqueCol) as dups from MYTABLE t1 join MYTABLE t2 on t1.uCol = t2.uCol;

   There should be no rows returned if file B is unique. Fix B if the information is not unique using details from the selection.

5. Load the fixed B file into MYFILE.

6. Drop table TEMPTABLE.

7. Repeat steps 3-6 for the rest of the set for each file prior to loading the data to the real MYTABLE instance.